Proceedings ArticleDOI
Controlling an arduino robot using Brain Computer Interface
Parth Gargava,Karan Sindwani,Sumit Soman +2 more
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TLDR
This paper establishes an application to control a robot on the Arduino platform by the use of a BCI system, which does not require training for individual users and achieves around 96% accuracy using computationally inexpensive feature extraction and classification techniques.Abstract:
The ability to acquire Electroencephalogram (EEG) signals from the brain has led to the development of Brain Computer Interfaces (BCI), which capture signals generated by the physical processes in the brain and use them to control external devices. In this paper, we establish an application to control a robot on the Arduino platform by the use of a BCI system, which does not require training for individual users. We present the design and development of a BCI processing pipeline built on open-source platforms using the Emotiv EEG headset. Our system achieves around 96% accuracy using computationally inexpensive feature extraction and classification techniques, namely, band power and Support Vector Machines (SVM). We are also able to guide a robot's movement efficiently using multiple intents.read more
Citations
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Book ChapterDOI
Towards EEG-Based Brain-Controlled Modular Robots: Preliminary Framework by Interfacing OpenVIBE, Python and V-REP for Simulate Modular Robot Control
TL;DR: This study presentation will focus on how to control the modular robot in V-REP environment by using Python language which can be used for interfacing with BCI system created in OpenVIBE software and the simulated robot configuration.
Proceedings ArticleDOI
Wireless EEG-based Fan Speed Control
TL;DR: In this paper, a wireless neuro-based fan that uses intention via EEG signals to control the fan speed by transmitting the EEG and control signals through Bluetooth is described, which can help the disable people who are limbless or paralyzed to be independent.
Proceedings ArticleDOI
AI Based Smart Cleaner with IOT Integration
TL;DR: In this paper , an automatic floor cleaner that uses an Arduino Nano and hand gestures from artificial intelligence is presented, and three ultrasonic sensors, an Arduino microcontroller, two tools with DC motors, an RF 433 module, and an accelerometer make up the system.
Proceedings ArticleDOI
Design and implementation of intelligent laboratory control system based on Arduino
TL;DR: In this paper, an intelligent laboratory control system platform based on the Arduino was designed and developed according to the software development process to set lab reservation, access control, network attendance and other functions in one.
Dissertation
A low complexity algorithm to control a robotic arm using the emotiv EPOC headset
TL;DR: A low complexity algorithm which uses the Emotiv EPOC headset to measure the difference of electrostatic potential in the head of an individual, computes the Short Time Fourier Transform of the signal, and calculates the area of a parametric curve in a 2D event space to perform the recognition of a single eye and both eyes winks.
References
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Brain-computer interfaces for communication and control
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